Spatial Analysis training is available as "onsite live training" or "remote live training". Onsite live Spatial Analysis training can be carried out locally on customer premises in Denmark or in NobleProg corporate training centers in Denmark. Remote live training is carried out by way of an interactive, remote desktop.

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Testimonials

★★★★★

★★★★★

The exercises combined with the experienced help of the trainer

Proximus

Course: Python Programming

The fact that we could practice a lot. Even though for me being a newbe the pace was to fast and explanation too few. However, probably due to the mixed knowkedge level of the students attending the class.

Proximus

Course: Python Programming

Good pace and knowledge demostrated by trainer. Exercises and examples were relevant for our line of work.

Tania Crespo - Grafton Merchanting GB

Course: Creating Dashboards Using Microsoft Power BI

The DAX logic, very useful to know more about it

Illya Teideman - Grafton Merchanting GB

Course: Creating Dashboards Using Microsoft Power BI

The exercises were great, really engaging and very hands on which allowed more of the information to be absorbed

Rajiv Pattar - Grafton Merchanting GB

Course: Creating Dashboards Using Microsoft Power BI

Trainer obviously had a great holistic understanding of programming.

Crux Product Design

Course: Python Programming Fundamentals

I enjoyed the sentinal analysis/ data science aspect of the course.

Jake Hamilton - Scottish Government

Course: Python Programming

pace and explanations

Centric IT Solutions Lithuania

Course: Advanced Python

His deep knowledge about the subject

Course: MATLAB Fundamentals, Data Science & Report Generation

was really helpful and was willing to listen and provide what was needed. Provided card for questions to help once we use with our own data

shazad Yasin - Grafton Merchanting GB Ltd

Course: Creating Dashboards Using Microsoft Power BI

Costas covered all of the key areas of Power BI. He was very willing to spend additional time focusing on areas that were key to our business.

Dominic Harte - Grafton Merchanting GB Ltd

Course: Creating Dashboards Using Microsoft Power BI

As I was the only delegate on my course, the trainer was able to pace accordingly which meant we could cover more ground on each day.

KNOWLEDGEPOOL GROUP LIMITED

Course: Creating Dashboards Using Microsoft Power BI

The visualisation power BI is able to create with such ease!

Tom Darley - Grafton Merchanting GB Ltd

Course: Creating Dashboards Using Microsoft Power BI

The trainer was great! If he would have more time I think we could have learned a lot more.

Zarim Jei Serrano - Cloudstaff Philippines, Inc.

Course: Python Programming Fundamentals

Exercises

Vince Christian Henson - Cloudstaff Philippines, Inc.

Course: Python Programming Fundamentals

I thought the training was very thorough and while we covered a lot of material, Martin made ample time for questions and gave good focus to each individual and their different requirements.

Jeán Thysse - Quidco

Course: Elasticsearch for Developers

Marcin knew exactly what he talking about and had proper hands on in-depth experience with the tools. He had answers to all our questions and made some really strong recommendations that we could start working towards with future projects and uses.

Conor Glasman - Quidco

Course: Elasticsearch for Developers

Doing the exercises. I really enjoyed the practicals.

Warren Stephen - Quidco

Course: Elasticsearch for Developers

It makes the trick. A good introduction (and more) to python.

jean-christophe GOLDBERG - Proximus

Course: Python Programming

Relaxed style. Help with the issues we were having with current setup.

Quidco

Course: Elasticsearch for Developers

The content relevnt and to the point

Qiniso Mdletshe - Quidco

Course: Elasticsearch for Developers

Trainer was very open minded about questions and tried to answer as many as possible.

Quidco

Course: Elasticsearch for Developers

The flexibilty and clear information

WAFEYA AlMadhoob - Tatweer Petroleum

Course: Advanced Python

I liked that we got a general overview of elastic and learned tons of things that could be applied in current project the first day.
I also liked that we went through current project code with a code review and mention improvements or/and stuff to think about or take up for discussion in the project on the second day.
I like that the training gave me a good base to continue delve into elastic search.

Mattias Hansson - Chalmers Tekniska Högskola AB

Course: Elasticsearch for Developers

The trainer's openness to questions and willingness to help/answer/explain.

Chalmers Tekniska Högskola AB

Course: Elasticsearch for Developers

He is very knowledgeable and could answer all the questions

Chalmers Tekniska Högskola AB

Course: Elasticsearch for Developers

The content.

HSBC Service Delivery (Polska) Sp. z o.o

Course: Python Programming

Pictures

HSBC Service Delivery (Polska) Sp. z o.o

Course: Python Programming

Willingness of Krzysztof to answer all questions.

HSBC Service Delivery (Polska) Sp. z o.o

Course: Python Programming

Live coding, helping with code and different bugs, explanation with examples

HSBC Service Delivery (Polska) Sp. z o.o

Course: Python Programming

Good interaction with audience, a lot of questions

Kinga Kalinowska - HSBC Service Delivery (Polska) Sp. z o.o

Course: Python Programming

The course has good proportion between theory and practice, knowledgeable trainer, a lot of training materials and user in practice.

HSBC Service Delivery (Polska) Sp. z o.o

Course: Python Programming

It covered many algorithms of ML and is useful to provide a track

HSBC Service Delivery (Polska) Sp. z o.o

Course: Python Programming

It was cery consistent

HSBC Service Delivery (Polska) Sp. z o.o

Course: Python Programming

All the exercises have been discussed

HSBC Service Delivery (Polska) Sp. z o.o

Course: Python Programming

Overall I liked course a lot. Good discussions. Sometimes to overall, but I understand that we were short of time.

HSBC Service Delivery (Polska) Sp. z o.o

Course: Python Programming

It covered systematically all the main topics of machine earning: both the theory and implementation. It gave me great background for further work. It also answered most of the questions about machine learning that I had up to this point.

HSBC Service Delivery (Polska) Sp. z o.o

Course: Python Programming

Trainer develops training based on participant's pace

Farris Chua

Course: Python Programming Fundamentals

Trainer develops training based on participant's pace

Farris Chua

Course: Data Analysis in Python using Pandas and Numpy

The notebooks were well-prepared and the examples were on point.

Course: Python Programming Fundamentals

The notebooks and examples were on point.

Course: Data Analysis in Python using Pandas and Numpy

The hands on

Course: Python Programming Fundamentals

The explanation provided is clear.

Course: Data Analysis in Python using Pandas and Numpy

The fact he had dif excel and data sheets with exercises for us to do.

Deepakie Singh Sodhi - Queens College, CUNY

Course: Excel For Statistical Data Analysis

Steve was willing to answer every questions and worked diligently to address any individual concerns or technical issues as they arose in the class. He also did a great job of presenting the technical details in a way that made it less intimidating to even the least tech savvy people in the room.
Personally, learning about some useful shortcuts in Excel that I didn't know about will certainly improve my overall workflow when using Excel in the future! I am so appreciative of those little details that I was exposed to during the two-day training.

Alan Gonzalez - Queens College, CUNY

Course: Excel For Statistical Data Analysis

all

Albert JACOB - Proximus

Course: Python Programming

Flask, dataclasses

Atos Global Delivery Center Polska Sp. Z o.o. Sp. K.,

Course: Advanced Python

R programming

Osden Jokonya - University of the Western Cape

Course: A Practical Introduction to Data Analysis and Big Data

Practical exercises

JOEL CHIGADA - University of the Western Cape

Course: A Practical Introduction to Data Analysis and Big Data

The pace was very good
Revising topics at the beginning of every session

deck.gl is an open-source, WebGL-powered library for exploring and visualizing data assets at scale. Created by Uber, it is especially useful for gaining insights from geospatial data sources, such as data on maps.

This instructor-led, live training introduces the concepts and functionality behind deck.gl and walks participants through the set up of a demonstration project.

By the end of this training, participants will be able to:

- Take data from very large collections and turn it into compelling visual representations- Visualize data collected from transportation and journey-related use cases, such as pick-up and drop-off experiences, network traffic, etc.- Apply layering techniques to geospatial data to depict changes in data over time- Integrate deck.gl with React (for Reactive programming) and Mapbox GL (for visualizations on Mapbox based maps).- Understand and explore other use cases for deck.gl, including visualizing points collected from a 3D indoor scan, visualizing machine learning models in order to optimize their algorithms, etc.

Audience

- Developers- Data scientists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

This instructor-led, live training in Denmark (onsite or remote) is aimed at field ecologists and conservation managers who wish to land survey and drone map with Pix4D.

By the end of this training, participants will be able to:

- Use end to end drone mapping processes and techniques.- Achieve high surveying accuracy.- Understand the fundamentals of global coordinate systems and GPS.- Generate and analyze survey output with Pix4D's image processing software.

Magellan is an open-source distributed execution engine for geospatial analytics on big data. Implemented on top of Apache Spark, it extends Spark SQL and provides a relational abstraction for geospatial analytics.

This instructor-led, live training introduces the concepts and approaches for implementing geospacial analytics and walks participants through the creation of a predictive analysis application using Magellan on Spark.

A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. The acronym GIS is sometimes used for geographic information science (GIScience) to refer to the academic discipline that studies geographic information systems and is a large domain within the broader academic discipline of geoinformatics.

The use of Python with GIS has substantially increased over the last two decades, particularly with the introduction of Python 2.0 series in 2000, which included many new programming features that made the language much easier to deploy. Since that time, Python has not only been utilized within commercial GIS such as products by Esri but also open source platforms, including as part of QGIS and GRASS. In fact, Python today is by far the most widely used language by GIS users and programmers.

This program covers the usage of Python and its advance libraries like geopandas, pysal, bokeh and osmnx to implement your own GIS features. The program also covers introductory modules around ArcGIS API, and QGIS toolboox.

A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. The acronym GIS is sometimes used for geographic information science (GIScience) to refer to the academic discipline that studies geographic information systems and is a large domain within the broader academic discipline of geoinformatics.

QGIS functions as geographic information system (GIS) software, allowing users to analyze and edit spatial information, in addition to composing and exporting graphical maps. QGIS supports both raster and vector layers; vector data is stored as either point, line, or polygon features. Multiple formats of raster images are supported, and the software can georeference images. To summarize it allows the users to Create, edit, visualise, analyse and publish geospatial information on Windows, Mac, Linux, BSD.

This program, in its first phase, introduces the QGIS interface for general usage. In the second phase, we introduce PyQGIS - the python libraries of QGIS that allows the integration of GIS functionalities in your python code or your python application, so that you may even create your own Python Plugin around a particular GIS functionality.